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    <name type="personal">
        <namePart type="given">Hou-Chiang</namePart>
        <namePart type="family">Tseng</namePart>
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    <name type="personal">
        <namePart type="given">Li-Yun</namePart>
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    <name type="personal">
        <namePart type="given">Hsueh-Chih</namePart>
        <namePart type="family">Chen</namePart>
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    <name type="personal">
        <namePart type="given">Yao-Ting</namePart>
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            <namePart type="given">Yi-Chin</namePart>
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            <publisher>The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)</publisher>
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    <abstract>Feature analysis of Chinese characters plays a prominent role in “character-based” education. However, there is an urgent need for a text analysis system for processing the difficulty of composing components for characters, primarily based on Chinese learners’ performance. To meet this need, the purpose of this research was to provide such a system by adapting a data-driven approach. Based on Chen et al.‘s (2011) Chinese Orthography Database, this research has designed and developed an system: Character Difficulty - Research on Multi-features (CD-ROM). This system provides three functions: (1) analyzing a text and providing its difficulty regarding Chinese characters; (2) decomposing characters into components and calculating the frequency of components based on the analyzed text; and (3) affording component-deriving characters based on the analyzed text and downloadable images as teaching materials. With these functions highlighting multi-level features of characters, this system has the potential to benefit the fields of Chinese character instruction, Chinese orthographic learning, and Chinese natural language processing.</abstract>
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%0 Conference Proceedings
%T The Design and Development of a System for Chinese Character Difficulty and Features
%A Haung, Jung-En
%A Tseng, Hou-Chiang
%A Chang, Li-Yun
%A Chen, Hsueh-Chih
%A Sung, Yao-Ting
%Y Chang, Yung-Chun
%Y Huang, Yi-Chin
%S Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)
%D 2022
%8 November
%I The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
%C Taipei, Taiwan
%G zho
%F haung-etal-2022-design
%X Feature analysis of Chinese characters plays a prominent role in “character-based” education. However, there is an urgent need for a text analysis system for processing the difficulty of composing components for characters, primarily based on Chinese learners’ performance. To meet this need, the purpose of this research was to provide such a system by adapting a data-driven approach. Based on Chen et al.‘s (2011) Chinese Orthography Database, this research has designed and developed an system: Character Difficulty - Research on Multi-features (CD-ROM). This system provides three functions: (1) analyzing a text and providing its difficulty regarding Chinese characters; (2) decomposing characters into components and calculating the frequency of components based on the analyzed text; and (3) affording component-deriving characters based on the analyzed text and downloadable images as teaching materials. With these functions highlighting multi-level features of characters, this system has the potential to benefit the fields of Chinese character instruction, Chinese orthographic learning, and Chinese natural language processing.
%U https://aclanthology.org/2022.rocling-1.32/
%P 256-262

Markdown (Informal)

[The Design and Development of a System for Chinese Character Difficulty and Features](https://aclanthology.org/2022.rocling-1.32/) (Haung et al., ROCLING 2022)

• The Design and Development of a System for Chinese Character Difficulty and Features (Haung et al., ROCLING 2022)

ACL

• Jung-En Haung, Hou-Chiang Tseng, Li-Yun Chang, Hsueh-Chih Chen, and Yao-Ting Sung. 2022. The Design and Development of a System for Chinese Character Difficulty and Features. In Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022), pages 256–262, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).